Genome-wide analysis of hepatic LRH-1 reveals a promoter binding preference and suggests a role in regulating genes of lipid metabolism in concert with FXR

<p>Abstract</p> <p>Background</p> <p>In a previous genome-wide analysis of FXR binding to hepatic chromatin, we noticed that an extra nuclear receptor (NR) half-site was co-enriched close to the FXR binding IR-1 elements and we provided limited support that the monomeric LRH-1 receptor that binds to NR half-sites might function together with FXR to activate gene expression.</p> <p>Results</p> <p>To analyze the global pattern for LRH-1 binding and to determine whether it might associate with FXR on a whole genome-wide scale, we analyzed LRH-1 binding to the entire hepatic genome using a non-biased genome-wide ChIP-seq approach. We identified over 10,600 LRH-1 binding sites in hepatic chromatin and over 20% were located within 2 kb of the 5' end of a known mouse gene. Additionally, the results demonstrate that a significant fraction of the genome sites occupied by LRH-1 are located close to FXR binding sites revealed in our earlier study. A Gene ontology analysis revealed that genes preferentially enriched in the LRH-1/FXR overlapping gene set are related to lipid metabolism. These results demonstrate that LRH-1 recruits FXR to lipid metabolic genes. A significant fraction of FXR binding peaks also contain a nuclear receptor half-site that does not bind LRH-1 suggesting that additional monomeric nuclear receptors such as RORs and NR4As family members may also target FXR to other pathway selective genes related to other areas of metabolism such as glucose metabolism where FXR has also been shown to play an important role.</p> <p>Conclusion</p> <p>These results document an important role for LRH-1 in hepatic metabolism through acting predominantly at proximal promoter sites and working in concert with additional nuclear receptors that bind to neighboring sites</p

Shape-selected bimetallic nanoparticle electrocatalysts: evolution of their atomic-scale structure, chemical composition, and electrochemical reactivity under various chemical environments

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Solid surfaces generally respond sensitively to their environment. Gas phase or liquid phase species may adsorb and react with individual surface atoms altering the solid-gas and solid-liquid electronic and chemical properties of the interface. A comprehensive understanding of chemical and electrochemical interfaces with respect to their responses to external stimuli is still missing. The evolution of the structure and composition of shape-selected octahedral PtNi nanoparticles (NPs) in response to chemical (gas-phase) and electrochemical (liquid-phase) environments was studied, and contrasted to that of pure Pt and spherical PtNi NPs. The NPs were exposed to thermal annealing in hydrogen, oxygen, and vacuum, and the resulting NP surface composition was analyzed using X-ray photoelectron spectroscopy (XPS). In gaseous environments, the presence of O2 during annealing (300 °C) lead to a strong segregation of Ni species to the NP surface, the formation of NiO, and a Pt-rich NP core, while a similar treatment in H2 lead to a more homogenous Pt-Ni alloy core, and a thinner NiO shell. Further, the initial presence of NiO species on the as-prepared samples was found to influence the atomic segregation trends upon low temperature annealing (300 °C). This is due to the fact that at this temperature nickel is only partially reduced, and NiO favors surface segregation. The effect of electrochemical cycling in acid and alkaline electrolytes on the structure and composition of the octahedral PtNi NPs was monitored using image-corrected high resolution transmission electron microscopy (TEM) and high-angle annular dark field scanning TEM (HAADF-STEM). Sample pretreatments in surface active oxygenates, such as oxygen and hydroxide anions, resulted in oxygen-enriched Ni surfaces (Ni oxides and/or hydroxides). Acid treatments were found to strongly reduce the content of Ni species on the NP surface, via its dissolution in the electrolyte, leading to a Pt-skeleton structure, with a thick Pt shell and a Pt-Ni core. The presence of Ni hydroxides on the NP surface was shown to improve the kinetics of the electrooxidation of CO and the electrocatalytic hydrogen evolution reactions. The affinity to water and the oxophilicity of Ni hydroxides are proposed as likely origin of the observed effects.DFG, EXC 314, Unifying Concepts in Catalysi

Murine Gamma-herpesvirus Immortalization of Fetal Liver-Derived B Cells Requires both the Viral Cyclin D Homolog and Latency-Associated Nuclear Antigen

Human gammaherpesviruses are associated with the development of lymphoproliferative diseases and B cell lymphomas, particularly in immunosuppressed hosts. Understanding the molecular mechanisms by which human gammaherpesviruses cause disease is hampered by the lack of convenient small animal models to study them. However, infection of laboratory strains of mice with the rodent virus murine gammaherpesvirus 68 (MHV68) has been useful in gaining insights into how gammaherpesviruses contribute to the genesis and progression of lymphoproliferative lesions. In this report we make the novel observation that MHV68 infection of murine day 15 fetal liver cells results in their immortalization and differentiation into B plasmablasts that can be propagated indefinitely in vitro, and can establish metastasizing lymphomas in mice lacking normal immune competence. The phenotype of the MHV68 immortalized B cell lines is similar to that observed in lymphomas caused by KSHV and resembles the favored phenotype observed during MHV68 infection in vivo. All established cell lines maintained the MHV68 genome, with limited viral gene expression and little or no detectable virus production - although virus reactivation could be induced upon crosslinking surface Ig. Notably, transcription of the genes encoding the MHV68 viral cyclin D homolog (v-cyclin) and the homolog of the KSHV latency-associated nuclear antigen (LANA), both of which are conserved among characterized γ2-herpesviruses, could consistently be detected in the established B cell lines. Furthermore, we show that the v-cyclin and LANA homologs are required for MHV68 immortalization of murine B cells. In contrast the M2 gene, which is unique to MHV68 and plays a role in latency and virus reactivation in vivo, was dispensable for B cell immortalization. This new model of gammaherpesvirus-driven B cell immortalization and differentiation in a small animal model establishes an experimental system for detailed investigation of the role of gammaherpesvirus gene products and host responses in the genesis and progression of gammaherpesvirus-associated lymphomas, and presents a convenient system to evaluate therapeutic modalities

Toward a More Accurate Genome: Algorithms for the Analysis of High-Throughput Sequencing Data

High-throughput sequencing enables basic and translational biology to query the mechanics of both life and disease at single-nucleotide resolution and with breadth that spans the genome. This revolutionary technology is a major tool in biomedical research, impacting our understanding of life's most basic mechanics and affecting human health and medicine. Unfortunately, this important technology produces very large, error-prone datasets that require substantial computational processing before experimental conclusions can be made. Since errors and hidden biases in the data may influence empirically-derived conclusions, accurate algorithms and models of the data are critical. This thesis focuses on the development of statistical models for high-throughput sequencing data which are capable of handling errors and which are built to reflect biological realities.First, we focus on increasing the fraction of the genome that can be reliably queried in biological experiments using high-throughput sequencing methods by expanding analysis into repeat regions of the genome. The method allows partial observation of the gene regulatory network topology through identification of transcription factor binding sites using Chromatin Immunoprecipitation followed by high-throughput sequencing (ChIP-seq). Binding site clustering, or "peak-calling", can be frustrated by the complex, repetitive nature of genomes. Traditionally, these regions are censored from any interpretation, but we re-enable their interpretation using a probabilistic method for realigning problematic DNA reads.Second, we leverage high-throughput sequencing data for the empirical discovery of underlying epigenetic cell state, enabled through analysis of combinations of histone marks. We use a novel probabilistic model to perform spatial and temporal clustering of histone marks and capture mark combinations that correlate well with cell activity. A first in epigenetic modeling with high-throughput sequencing data, we not only pool information across cell types, but directly model the relationship between them, improving predictive power across several datasets.Third, we develop a scalable approach to genome assembly using high-throughput sequencing reads. While several assembly solutions exist, most don't scale well to large datasets, requiring computers with copious memory to assemble large genomes. Throughput continues to increase and the large datasets available today and in the near future will require truly scalable methods. We present a promising distributed method for genome assembly which distributes the de Bruijn graph across many computers and seamlessly spills to disk when main memory is insufficient. We also show novel graph cleaning algorithms which should handle increased errors from large datasets better than traditional graph structure-based cleaning.High-throughput sequencing plays an important role in biomedical research, and has already affected human health and medicine. Future experimental procedures will continue to rely on statistical methods to provide crucial error and bias correction, in addition to modeling expected outcomes. Thus, further development of robust statistical models is critical to the future high-throughput sequencing, ensuring a strong foundation for correct biological conclusions

Discovering and mapping chromatin states using a tree hidden Markov model

Abstract New biological techniques and technological advances in high-throughput sequencing are paving the way for systematic, comprehensive annotation of many genomes, allowing differences between cell types or between disease/normal tissues to be determined with unprecedented breadth. Epigenetic modifications have been shown to exhibit rich diversity between cell types, correlate tightly with cell-type specific gene expression, and changes in epigenetic modifications have been implicated in several diseases. Previous attempts to understand chromatin state have focused on identifying combinations of epigenetic modification, but in cases of multiple cell types, have not considered the lineage of the cells in question. We present a Bayesian network that uses epigenetic modifications to simultaneously model 1) chromatin mark combinations that give rise to different chromatin states and 2) propensities for transitions between chromatin states through differentiation or disease progression. We apply our model to a recent dataset of histone modifications, covering nine human cell types with nine epigenetic modifications measured for each. Since exact inference in this model is intractable for all the scale of the datasets, we develop several variational approximations and explore their accuracy. Our method exhibits several desirable features including improved accuracy of inferring chromatin states, improved handling of missing data, and linear scaling with dataset size. The source code for our model is available at http:// http://github.com/uci-cbcl/tree-hm

Biallelic genome modification in F0 Xenopus tropicalis embryos using the CRISPR/Cas system

Gene inactivation is an important tool for correlation of phenotypic and genomic data, allowing researchers to infer normal gene function based on the phenotype when the gene is impaired. New and better approaches are needed to overcome the shortfalls of existing methods for any significant acceleration of scientific progress. We have adapted the CRISPR/Cas system for use in Xenopus tropicalis and report on the efficient creation of mutations in the gene encoding the enzyme tyrosinase, which is responsible for oculocutaneous albinism. Biallelic mutation of this gene was detected in the F0 generation, suggesting targeting efficiencies similar to that of TALENs. We also find that off-target mutagenesis seems to be negligible, and therefore, CRISPR/Cas may be a useful system for creating genome modifications in this important model organism

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

BACKGROUND: Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. RESULTS: We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. CONCLUSION: Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells